In the conventional image forming apparatuses (or image recording apparatuses) such as the printers, facsimile machines and copying machines, a digital image data which is formed is a bi-level image made up of “1”s and “0”s or, dots having ON and OFF states. But due to progresses made in image forming engines and the demands for realizing a high-quality image, it is becoming more popular to form plural-level (or multi-level) image data which represent each pixel in a plurality of gradation levels.
In this specification, the “plural-level” is used similarly to the generally used terms “multi-level” and “bi-level”, but the amount of information included in the plural-level image data is greater than that of the bi-level image data but less than or equal to that of the multi-level image data. Normally, when carrying out an image processing, the multi-level image data which is used as the input image data has an amount of information on the order of approximately 8 bits (256 values) per pixel. But in a case where the image forming apparatus which actually forms an image based on the input image data is only capable of representing approximately 1 bit to 3 bits per pixel, the image data has more levels than “bi-level” but only has a small number of levels as a “multi-level”, and is thus referred to as a “plural-level image data”.
For example, in the ink-jet printer, the tone modulation method which changes the tone of the ink, the dot size modulation method which uses dots having different sizes, and the method which uses both the tone modulation method and the dot size modulation method are most commonly used at the present.
In the ink-jet printer, a pressure generating means of an ink-jet head is formed by a heating resistor which generates air bubbles in the case of the thermal ink-jet, a piezoelectric element in the case of the piezoelectric ink-jet, and an electrostatic element in the case of the electrostatic ink-jet. The dot size is controlled by controlling an amplitude, a pulse width, a number of pulses and the like of a driving voltage which is applied to electrodes of such pressure generating means. However, due to the spreading of the ink and the like, the dot size control can realize only four states at the most with a satisfactory reproducibility, namely, a large dot, a medium dot, a small dot and no dot.
FIGS. 1A through 1C are diagrams for explaining dot layout patterns which are used when carrying out the general binarization process and the plural-level process. FIG. 1A shows the dot reproduction for a case where the binarization process is carried out, FIG. 1B shows the dot reproduction for a case where the plural-level process (tone modulation) is carried out, and FIG. 1C shows the dot reproduction for a case where the plural-level process (dot size modulation) is carried out. In FIGS. 1A through 1C, black circular marks indicate the dots, and circular marks with hatching indicate dots having a lower tone than the dots indicated by the black circular marks. Further, in FIGS. 1A through 1C, the dot pattern on the left indicates a low (light) tone, the dot pattern in the middle indicates a medium tone, and the dot pattern on the right indicates a high (dark or maximum) tone.
According to the dot reproduction shown in FIGS. 1A through 1C, the amount of information is basically determined by the controllable dot size. The amount of information increases as the number of controllable dot sizes increases, to thereby enable reproduction of a high-quality picture close to the original image data. But as described above, the number of controllable dot sizes is only on the order of 1 to 3 (or 4 when 0 is included) in the case of most ink-jet printers. It is possible to improve the picture quality to a certain extent by combining the dot size modulation method and the tone modulation method, but the load is then put on the coloring agents (dyes) and recording units in order to achieve the desired picture quality. Consequently, due to cost and size restrictions on the image forming apparatus, it is only possible to improve the picture quality to two times at the most, even when the dot size modulation method and the tone modulation method are combined.
In order to compensate for the insufficient amount of information per pixel, a pseudo gradation representation which is generally referred to as a halftone process is used as a technique for controlling the number of dots per unit area. The pseudo gradation representation represents the number of dots which are arranged as a tone, and represents a large number of gradation levels by changing the density of the dot. The halftone method includes the dither method and the error diffusion method.
The dither method is popularly used for the pseudo gradation representation, and typical dither methods are the systematic dither method and the random dither method. The systematic dither method sets a sub matrix (or dither matrix) made up of n×n threshold values, and overlaps this dither matrix with the input image to compare the tone level of each pixel and the corresponding threshold value in the dither matrix. A bi-level representation is made by setting a value “1” (black) if the pixel value of the input image is greater than or equal to the corresponding threshold value, and setting a value “0” (white) if the pixel value of the input image is less than the corresponding threshold value. If the processing of n×n pixels ends, the image is formed by repeatedly carrying out the above described process while successively moving the dither matrix to the position of the next n×n pixels.
FIGS. 2A, 2B and 2C are diagrams for explaining the systematic dither method. For example, with respect to an input multi-level image data shown in FIG. 2A, a comparison is made with an n×n dither matrix shown in FIG. 2B which is created by a predetermined method. Hence, only the pixels of the input image having values greater than or equal to the corresponding threshold values are replaced by dots as shown in FIG. 2C. Of course, it is possible to replace only the pixels of the input image having values less than the corresponding threshold values by the dots.
FIG. 2C shows a case where the dots are bi-level, that is, the dots have an ON state or an OFF state. However, the dots may be made to have plural-levels by sectioning the reproducible gradation region into small, medium and large dots as shown in FIG. 3. FIG. 3 is a diagram showing a correspondence between size modulated dots and dither masks. In this case, a threshold value matrix corresponding to the dot size is used for each of the small, medium and large dots, when making the comparison with the input image data to make the replacement to the dots. FIGS. 4A, 4B and 4C are diagrams respectively showing the threshold value matrixes for the small, medium and large dots.
On the other hand, the random dither method generates a random value with respect to each pixel of the input image and uses the generated value as the threshold value. However, the image formed using the random dither method is not very smooth in general, and is unsuited for improving the picture quality as compared to the systematic dither method.
Furthermore, the pseudo gradation representation may be made by the error diffusion method. However, the error diffusion method requires a considerably complex process when compared to the dither methods.
FIG. 5 is a diagram for explaining a bi-level error diffusion technique. In FIG. 5, a step ST1 carries out an error diffusion process shown. Black circular marks indicate the pixels having the dots which are ON, circular marks indicated by a dotted line indicate pixels having the dots which are OFF, and numerals indicate the pixels which are not yet processed. A step ST2 carries out a threshold value process shown. exy denotes an error generated by the threshold value process, and ※ indicates a target pixel which is the target of the next error diffusion process.
A step ST3 multiplies an error weight matrix EWM to the error values of the processed peripheral pixels, and calculates a corrected pixel value CPV by adding the error weight matrix EWM to the value of the next processing target pixel. ※ indicates the target pixel which is the target of the next error diffusion process. A step ST4 compares a fixed (or variable) threshold value and the corrected pixel value CPV, and calculates the ON and OFF states of the dots and the error value (exy), where non-segmented image is indicated by “255” and solid color is indicated by “0”.
Hence, the error diffusion method carries out the threshold value process for each pixel and holds the error while reflecting the error to the latter calculations at a predetermined ratio. Hence, the error diffusion method can feed back to the output image even the amount of information which is forcibly discarded in the dither process, thereby making it possible to obtain a picture quality which is improved over the dither image from the point of view of the resolution and the like.
Developments are being made to further improve the resolution while obtaining a high picture quality by the dither methods and error diffusion method described above. This is because the individual dot size and separation of the dots become small as the resolution becomes high, and the dot patterns created by the dither method or the error diffusion method become more difficult to recognize. If the dot pattern is not recognizable by the human eye, this is equivalent to making a multi-level representation by 1 pixel. In ink-jet printers which have been recently developed, a resolution of 2880 dpi has been realized.
Although the picture quality is improved by improving the resolution, the cost of the recording unit increases and the recording (printing) speed decreases. In order to realize the high resolution, a high-precision control is required to maintain the high dot position accuracy, in addition to the requirement to form dots which are smaller than the conventionally used dots. As a result, the cost of the image forming apparatus inevitably becomes high. In addition, when using the same recording unit, it takes more time to make the recording for the higher resolution because the coverage area per dot becomes smaller for the higher resolution.
But in actual practice, there are cases where a high picture quality is preferred over the recording speed and cost, and also cases where the desired recording speed and cost are preferred as long as a picture quality higher than a predetermined quality is obtainable. In other words, it is not always the case that the high picture quality is required.
But up to now, all emphasis was put on further improving the dot forming speed and further improving the mounting density of the recording units by means of hardware, while maintaining the high resolution. In other words, the emphasis was put on increasing the recording speed of the image forming apparatuses which are designed for the high picture quality, and not on improving the picture quality of the inexpensive image forming apparatuses which have low resolutions.
When increasing the recording speed of the image forming apparatus which is designed for the high picture quality, it is impossible to realize considerable improvement in the recording speed unless the recording sequence itself is modified, because of the cost restrictions and restrictions on the mounting area. In addition, when the recording sequence is modified, it is impossible to apply the image processing for the high resolution unless the image processing itself is also modified. As a result, it is necessary to modify the image processing depending on the modified recording sequence. But in the conventional image forming apparatuses, only a simple image processing is applied, and no attempts were made to positively improve the picture quality.